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---
library_name: transformers
license: mit
base_model: vblagoje/bart_lfqa
tags:
- generated_from_trainer
model-index:
- name: BART_HYDROGEN_GENERATION_QA
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BART_HYDROGEN_GENERATION_QA
This model is a fine-tuned version of [vblagoje/bart_lfqa](https://huggingface.co/vblagoje/bart_lfqa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5046
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2697 | 0.2092 | 100 | 0.5574 |
| 1.0628 | 0.4184 | 200 | 0.5151 |
| 1.0037 | 0.6276 | 300 | 0.5066 |
| 0.9652 | 0.8368 | 400 | 0.4842 |
| 0.9284 | 1.0460 | 500 | 0.4974 |
| 0.8272 | 1.2552 | 600 | 0.5046 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
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